Apparatus and method for personalized delivery of content from multiple data sources

ABSTRACT

A non-transitory computer readable storage medium includes instructions to collect explicit feedback from a user regarding user content preferences. Multiple data sources are monitored. Topics associated with the multiple data sources are classified. The importance of the topics to the user is characterized. Content is delivered to the user when a selected topic exceeds an importance threshold for the user. Implicit feedback from the user that characterizes refined user content preferences is tracked. The instructions to characterize the importance of topics evaluates the explicit feedback and the implicit feedback.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. Provisional Patent Application61/349,679, filed May 28, 2010, the contents of which are incorporatedherein.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with government support under contract numberNBCHD030010 awarded by the United States Government Department of theInterior and with the U.S. Air Force Research Laboratory underGovernment contract number FA8750-09-D-0183. The Government has certainrights in this invention.

FIELD OF THE INVENTION

This invention relates generally to information distribution in computernetworks. More particularly, this invention relates to techniques forpersonalized delivery of content from multiple data sources.

BACKGROUND OF THE INVENTION

It is a challenge to identify relevant information in a large set ofdocuments, especially where the contents of the documents are not knownin advance. Examples of such sets of documents include RSS or newsfeeds, incoming mail, discussion boards or blogs, or streams of chat,twitter tweets, or transcripts of audio.

There are existing techniques to sort information in large data feeds.These techniques use statistical methodologies to determine theinformation that is most popular with large numbers of users.

It would be desirable to develop a new sorting paradigm that focuses onpersonal relevance of information instead of the relevance ofinformation to a large number of users.

SUMMARY OF THE INVENTION

A non-transitory computer readable storage medium includes instructionsto collect explicit feedback from a user regarding user contentpreferences. Multiple data sources are monitored. Topics associated withthe multiple data sources are classified. The importance of the topicsto the user is characterized. Content is delivered to the user when aselected topic exceeds an importance threshold for the user. Implicitfeedback from the user that characterizes refined user contentpreferences is tracked. The instructions to characterize the importanceof topics evaluates the explicit feedback and the implicit feedback.

BRIEF DESCRIPTION OF THE FIGURES

The invention is more fully appreciated in connection with the followingdetailed description taken in conjunction with the accompanyingdrawings, in which:

FIG. 1 illustrates a system configured in accordance with an embodimentof the invention.

FIG. 2 illustrates processing operations associated with an embodimentof the invention.

Like reference numerals refer to corresponding parts throughout theseveral views of the drawings.

DETAILED DESCRIPTION OF THE INVENTION

This invention monitors information sources and identifies documentsthat are specifically relevant to the individual user's interests. Thesystem processes documents collected from diverse sources which areeither unclassified or classified only on very broad topics rather thanto specific customized user needs (e.g., RSS feeds, blog firehoses,search engine dynamic feeds, etc). The user would normally have toperuse all the articles or use traditional search to find the mostrelevant information. If the feed is sparse in relevant information, theuser may waste a lot of time or may stop following the feed. Thisinvention can improve the user's efficiency by authoring a digested feedof content containing only the most relevant information.

A model of the user's interests is built by observing the articles thatare read. By reading an article, the user provides implicit feedback ofthe article's relevance. Alternatively or in addition, the user canprovide explicit feedback. A user can also identify articles asbelonging to one of an optional set of user-defined topics. The feedbackalso allows the system to build a model of the topics. The use ofimplicit feedback minimizes the user's cognitive load while gaining thebenefit of the learning technology.

Using the models and a classifier, the topic and relevance of newarticles are predicted. The user only needs to identify a topic ofinterest, which can be done by typing in key words or adding the weblink/url of a story of interest. For example, if the user is interestedin the 2012 Presidential Campaign and Election, the user can type in aseries of descriptors, including 2012 presidential election, Obama, GOP,New Hampshire primary, and so on. Based on this input, the technologywill continuously scan streams of new content, identifying those storiesthat are relevant and deliver the content to the user. The user willthen “score” these stories either through implicit actions (e.g.,reading, savings, sharing, or deleting) or explicitly (e.g., by offeringa “thumbs up” or “thumbs down,” depending on the perceived value of thiscontent to the individual user).

The system learns based on this feedback, giving the user more of whatis liked, and less of what is disliked. In this simple example, one usermy only want information about a democratic candidate, a second user mayonly want information about a republican candidate, and a third user mayonly want information about a green party candidate. The system quicklylearns these preferences, adjusts, and continues to refine the selectionwith each instance of user feedback.

Because this system focuses on the relevant content, the user can readarticles only in specific areas of interest, without having to guessspecific sources (e.g., websites, RSS feeds, etc.) and without having tosift through streams of irrelevant, uninteresting content.

Once the technology has been delivered to the user, this system providesthe user a rich tool set, providing capabilities to allow savingarticles to a reading list, annotating the articles, or sharing withassociates via email, or by posting on popular social media services(e.g., Twitter, Facebook, etc.) Features of the technology include:

-   -   1. The supply of personalized information to a user based on a        users personal interest, not by what is deemed popular based on        statistical determination of what is “popular.”    -   2. Unlike techniques which require a user to identify specific        sources of information (specific RSS feeds, for example), this        technology culls information from an extremely broad range of        sources, delivering to the users only that which is most        important.    -   3. This technology adapts based on the users implicit and        explicit behavior. With each instance of use, the technology        becomes “smarter,” continuously refining the type of content        delivered to the user.    -   4. The information is persistent. Unlike search, which is a one        time event, this technology establishes a permanent topical        information “container,” to which content of increasing        relevance will be perpetually delivered until the user decides        to terminate the collection.    -   5. Finally, once the information has been delivered to the        user's topical container, it allows the user to save individual        articles to a reading list, or share articles with associates        via email, or through popular social media applications (e.g.,        Twitter, Facebook, etc.).

The invention is more fully appreciated with reference to FIG. 1. FIG. 1illustrates a system 100 configured in accordance with an embodiment ofthe invention. The system 100 includes a client device 102 and a servercomputer 104 linked by a transmission channel 106, which may be anywired or wireless transmission channel. A variety of data sources 108_1through 108_N are also connected to the transmission channel 106. By wayof example, the data sources 108 may include an RSS source, a chatsource, shared files, email, and the like.

The client device 102 includes standard components, such as a CentralProcessing Unit 110 and input/output devices 112 connected via a bus114. The input/output devices may include a keyboard, mouse, touchdisplay and the like. A network interface card 116 is also connected tothe bus 114 to provide a communication link with the transmissionchannel 106. A memory 120 is also connected to the bus 114. The memorystores a communication module 122, which may be a browser or applicationto facilitate network communications. The client 102 may be a computer,smart phone, personal digital assistant or similar device.

The server 104 also includes standard components, such as a networkinterface circuit 166, input/output devices 164 and a central processingunit 160 connected via a bus 162. A memory 170 is also connected to thebus 162. The memory 170 includes executable instructions to implementoperations of the invention. In one embodiment, the memory 170 stores atopic classifier 172. The topic classifier 172 classifies topicsobserved from the data sources 108. A topic classifier utilizes atraining set of data containing known observations for a sub-populationto identify the sub-population to which new observations belong. Newindividual items are placed into groups by the classifier based uponquantitative information on one or more measurements, traits orcharacteristics established by the training set.

The importance classifier 174 includes instructions to characterize theimportance of identified topics to a particular user. Thisclassification may be based upon explicit feedback 176 provided by theuser and implicit feedback 178 gathered by observing activities of theuser.

FIG. 2 illustrates processing operations associated with an embodimentof the invention. Initially, explicit feedback is collected 200. Forexample, the explicit feedback may be collected from a web form thatsolicits a user's interests. Server 104 may deliver the form to client102 and then collect the responses from the user utilizing the client102.

Next, data sources are monitored 202. For example, server 104 maymonitor data sources 108_1 through 108_N. Topics within the monitoreddata sources are then classified 204. After classification, theimportance of individual topics is characterized 206. If a topic and itsimportance exceeds a pre-determined threshold for the user, then thecontent is delivered to the user 208. The user's interaction with thecontent is then tracked to develop implicit feedback 210. Implicitfeedback may also be gathered by observing general operations of theuser (e.g., who the user is communicating with, what topics are commonlyaddressed, etc.).

An embodiment of the present invention relates to a computer storageproduct with a computer readable storage medium having computer codethereon for performing various computer-implemented operations. Themedia and computer code may be those specially designed and constructedfor the purposes of the present invention, or they may be of the kindwell known and available to those having skill in the computer softwarearts. Examples of computer-readable media include, but are not limitedto: magnetic media such as hard disks, floppy disks, and magnetic tape;optical media such as CD-ROMs, DVDs and holographic devices;magneto-optical media; and hardware devices that are speciallyconfigured to store and execute program code, such asapplication-specific integrated circuits (“ASICs”), programmable logicdevices (“PLDs”) and ROM and RAM devices. Examples of computer codeinclude machine code, such as produced by a compiler, and filescontaining higher-level code that are executed by a computer using aninterpreter. For example, an embodiment of the invention may beimplemented using JAVA®, C++, or other object-oriented programminglanguage and development tools. Another embodiment of the invention maybe implemented in hardwired circuitry in place of, or in combinationwith, machine-executable software instructions.

The foregoing description, for purposes of explanation, used specificnomenclature to provide a thorough understanding of the invention.However, it will be apparent to one skilled in the art that specificdetails are not required in order to practice the invention. Thus, theforegoing descriptions of specific embodiments of the invention arepresented for purposes of illustration and description. They are notintended to be exhaustive or to limit the invention to the precise formsdisclosed; obviously, many modifications and variations are possible inview of the above teachings. The embodiments were chosen and describedin order to best explain the principles of the invention and itspractical applications, they thereby enable others skilled in the art tobest utilize the invention and various embodiments with variousmodifications as are suited to the particular use contemplated. It isintended that the following claims and their equivalents define thescope of the invention.

The invention claimed is:
 1. A non-transitory computer readable storagemedium, comprising instructions to: collect explicit feedback from auser regarding textual content preferences; monitor a plurality ofdiverse data sources generating textual content, wherein the pluralityof diverse data sources include websites, RSS feeds, blogs and socialmedia services generating textual content; classify topics associatedwith the plurality of diverse data sources to form a model of topics;characterize the importance of the topics to the user to form a model ofuser interests; deliver textual content to the user when, based on themodel of topics and the model of user interests, a selected topicexceeds an importance threshold for the user; and track implicitfeedback from the user that characterizes refined textual contentpreferences; wherein the instructions to characterize the importance oftopics evaluates the explicit feedback and the implicit feedback.
 2. Thenon-transitory computer readable storage medium of claim 1 wherein theexplicit feedback is a web form that solicits the interests of the user.3. The non-transitory computer readable storage medium of claim 1wherein the explicit feedback is a thumb up or thumb down indicationfrom the user.
 4. The non-transitory computer readable storage medium ofclaim 1 wherein the implicit feedback is reading the textual content. 5.The non-transitory computer readable storage medium of claim 1 whereinthe implicit feedback is saving the textual content.
 6. Thenon-transitory computer readable storage medium of claim 1 wherein theimplicit feedback is sharing the textual content.
 7. The non-transitorycomputer readable storage medium of claim 1 wherein the implicitfeedback is deleting the textual content.
 8. The non-transitory computerreadable storage medium of claim 1 further comprising executableinstructions to form a container of textual content that continuouslyreceives textual content until the container is terminated.